With the constant development of computer technology, the multidimensional data analysis has been used widely in various data analysis platforms. The multidimensional data analysis is developed from OLAP (On-Line Analytical Processing) technology and the core of the OLAP. The purpose is to observe and analyze index variations from multi-dimensions to emphasize the demonstration of the obtained index data by some selected important dimensions.
In traditional OLAP service, two query service strategies are provided in general. One way is that some predetermindely fixed attribute compositions, i.e. some attribute compositions are predetermindely set and index data in accordance with the attribute compositions is obtained. When the query is received, the index data will be directly demonstrated to the user if the query comprises the attribute compositions. If the query does not comprise the predetermindely fixed attribute compositions, then no query service is provided. The other way is that no predetermindely fixed attribute compositions exist, and the calculation is executed starting from the stream-oriented data according to the attribute compositions in the query after receiving the query.
Nowadays, dimensions and attributes of every dimension become more and more with the increase of the stream-oriented data. The computing cost is high and the computing complexity is high under circumstance that index data of the respective attribute compositions is obtained by starting from the stream-oriented data.